A branch-and-cut method minimizes the pessimistic IEO regret loss directly for 0-1 combinatorial decision-focused learning, avoiding the need for a convex hull.
A synthetic data-plus- features driven approach for portfolio optimization,
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Pessimistic bilevel optimization approach for decision-focused learning
A branch-and-cut method minimizes the pessimistic IEO regret loss directly for 0-1 combinatorial decision-focused learning, avoiding the need for a convex hull.